Whole-brain patterns of 1H-magnetic resonance spectroscopy imaging in Alzheimer's disease and dementia with Lewy bodies

Acknowledgements We thank Craig Lambert for his help in processing the MRS data. The study was funded by the Sir Jules Thorn Charitable Trust (grant ref: 05/JTA) and was supported by the National Institute for Health Research (NIHR) Newcastle Biomedical Research Centre and the Biomedical Research Unit in Lewy Body Dementia based at Newcastle upon Tyne Hospitals National Health Service (NHS) Foundation Trust and Newcastle University and the NIHR Biomedical Research Centre and Biomedical Research Unit in Dementia based at Cambridge University Hospitals NHS Foundation Trust and the University of Cambridge.Peer reviewedPublisher PD

Characterization of Metabolic, Diffusion, and Perfusion Properties in GBM: Contrast-Enhancing versus Non-Enhancing Tumor.

BackgroundAlthough the contrast-enhancing (CE) lesion on T1-weighted MR images is widely used as a surrogate for glioblastoma (GBM), there are also non-enhancing regions of infiltrative tumor within the T2-weighted lesion, which elude radiologic detection. Because non-enhancing GBM (Enh-) challenges clinical patient management as latent disease, this study sought to characterize ex vivo metabolic profiles from Enh- and CE GBM (Enh+) samples, alongside histological and in vivo MR parameters, to assist in defining criteria for estimating total tumor burden.MethodsFifty-six patients with newly diagnosed GBM received a multi-parametric pre-surgical MR examination. Targets for obtaining image-guided tissue samples were defined based on in vivo parameters that were suspicious for tumor. The actual location from where tissue samples were obtained was recorded, and half of each sample was analyzed for histopathology while the other half was scanned using HR-MAS spectroscopy.ResultsThe Enh+ and Enh- tumor samples demonstrated comparable mitotic activity, but also significant heterogeneity in microvascular morphology. Ex vivo spectroscopic parameters indicated similar levels of total choline and N-acetylaspartate between these contrast-based radiographic subtypes of GBM, and characteristic differences in the levels of myo-inositol, creatine/phosphocreatine, and phosphoethanolamine. Analysis of in vivo parameters at the sample locations were consistent with histological and ex vivo metabolic data.ConclusionsThe similarity between ex vivo levels of choline and NAA, and between in vivo levels of choline, NAA and nADC in Enh+ and Enh- tumor, indicate that these parameters can be used in defining non-invasive metrics of total tumor burden for patients with GBM

Methodological consensus on clinical proton MRS of the brain: Review and recommendations

© 2019 International Society for Magnetic Resonance in Medicine Proton MRS (1H MRS) provides noninvasive, quantitative metabolite profiles of tissue and has been shown to aid the clinical management of several brain diseases. Although most modern clinical MR scanners support MRS capabilities, routine use is largely restricted to specialized centers with good access to MR research support. Widespread adoption has been slow for several reasons, and technical challenges toward obtaining reliable good-quality results have been identified as a contributing factor. Considerable progress has been made by the research community to address many of these challenges, and in this paper a consensus is presented on deficiencies in widely available MRS methodology and validated improvements that are currently in routine use at several clinical research institutions. In particular, the localization error for the PRESS localization sequence was found to be unacceptably high at 3 T, and use of the semi-adiabatic localization by adiabatic selective refocusing sequence is a recommended solution. Incorporation of simulated metabolite basis sets into analysis routines is recommended for reliably capturing the full spectral detail available from short TE acquisitions. In addition, the importance of achieving a highly homogenous static magnetic field (B0) in the acquisition region is emphasized, and the limitations of current methods and hardware are discussed. Most recommendations require only software improvements, greatly enhancing the capabilities of clinical MRS on existing hardware. Implementation of these recommendations should strengthen current clinical applications and advance progress toward developing and validating new MRS biomarkers for clinical use

Advanced parallel magnetic resonance imaging methods with applications to MR spectroscopic imaging

Parallel magnetic resonance imaging offers a framework for acceleration of conventional MRI encoding using an array of receiver coils with spatially-varying sensitivities. Novel encoding and reconstruction techniques for parallel MRI are investigated in this dissertation. The main goal is to improve the actual reconstruction methods and to develop new approaches for massively parallel MRI systems that take advantage of the higher information content provided by the large number of small receivers. A generalized forward model and inverse reconstruction with regularization for parallel MRI with arbitrary k-space sub-sampling is developed. Regularization methods using the singular value decomposition of the encoding matrix and pre-conditioning of the forward model are proposed to desensitize the solution from data noise and model errors. Variable density k-space sub-sampling is presented to improve the reconstruction with the common uniform sub-sampling. A novel method for massively parallel MRI systems named Superresolution Sensitivity Encoding (SURE-SENSE) is proposed where acceleration is performed by acquiring the low spatial resolution representation of the object being imaged and the stronger sensitivity variation from small receiver coils is used to perform intra-pixel reconstruction. SURE-SENSE compares favorably the performance of standard SENSE reconstruction for low spatial resolution imaging such as spectroscopic imaging. The methods developed in this dissertation are applied to Proton Echo Planar Spectroscopic Imaging (PEPSI) for metabolic imaging in human brain with high spatial and spectral resolution in clinically feasible acquisition times. The contributions presented in this dissertation are expected to provide methods that substantially enhance the utility of parallel MRI for clinical research and to offer a framework for fast MRSI of human brain with high spatial and spectral resolution

Water and lipid artifacts removal in MRSI data of the brain using new post-processing methods

Tese de mestrado integrado, Engenharia Biomédica e Biofísica (Sinais e Imagens Médicas) Universidade de Lisboa, Faculdade de Ciências 2016Espectroscopia de ressonância magnética (MRS), ao contrário de imagem de ressonância magnética (MRI), permite adquirir informação metabólica em vez de apenas informação morfológica. Imagem de MRS (MRSI) no cérebro permite detetar espectros de múltiplos voxels e, consequentemente, a heterogeneidade espacial de concentrações metabólicas, o que pode ser um indicador de doenças neurológicas e metabólicas. Contudo, MRSI é tecnicamente mais desafiante em campos magnéticos ultra altos havendo algumas limitações que impedem a implementação de MRSI em diagnóstico clínico. Como as concentrações dos metabolitos no corpo são muito mais baixas do que as dos lípidos e, especialmente, da água a sensibilidade de MRS na deteção dos metabolitos é muito mais baixa. Além disso, os sinais da água e dos lípidos são várias ordens de magnitude superiores às dos metabolitos, contaminando o espectro metabólico. Deste modo, é necessário utilizar técnicas de supressão de água e de lípidos. Todavia, devido à heterogeneidade de campo magnético causada por diferenças de suscetibilidade magnéticas nas interfaces ar-tecido, os sinais de água e dos lípidos podem sofrer um desvio da sua frequência, dificultando ainda mais a sua supressão. As técnicas mais usadas para supressão de água são a chemical-shift selective water suppression (CHESS) e a variable pulse power and optimized relaxation delays (VAPOR) que é baseada em CHESS. Embora a CHESS seja mais sensível a heterogeneidades de T1 e de B1, permite tempos de repetição mais curtos do que a VAPOR. No caso dos lípidos, técnicas como supressão de volume exterior (OVS) são muito usadas, porém necessitam de pulsos de radiofrequência (RF) adicionais e gradientes de desfasamento que aumentam o tempo de aquisição. Contudo, desenvolveu-se recentemente uma crusher coil que utiliza uma pequena corrente para gerar gradientes superficiais de desfasamento, criando uma distorção de campo magnético B0 que desfasa o sinal dos lípidos, permitindo tempos de aquisição mais curtos. A resolução espacial em MRSI é limitada não só pela baixa razão sinal-ruido (SNR) dos metabolitos, mas também pelo tempo necessário para codificação em fase das dimensões espaciais. Consequentemente, MRSI adquire-se com amostragem limitada do espaço k para manter tempos de aquisição aceitáveis. Os dados de MRSI necessitam de uma reconstrução com transformada de Fourier (FT) que, devido à amostragem limitada com zero-filling do espaço k, origina efeito de Gibbs ringing. A contaminação de sinal associada a este efeito é chamada de voxel bleeding (vazamento de sinal) e pode ser caracterizada usando a função de resposta ao impulso (PSF). A PSF é descrita por uma função seno cardinal, cuja largura a meia altura do pico principal corresponde ao tamanho efetivo do voxel. A contribuição do sinal pode ser positiva ou negativa e vai diminuindo com a distância à origem da PSF. No caso de a fonte de sinal estar no centro do voxel, não causará contaminação, pois os lobos laterais da função cruzam o valor zero no centro dos voxels adjacentes, ou seja, as contribuições cancelar-se-ão. Caso a fonte esteja localizada na borda do voxel, existirá uma propagação significativa do sinal para os voxels adjacentes. Filtros de apodização do espaço k permitem reduzir os lobos laterais da PSF e, consequentemente, a contaminação. Contudo, aumentam o tamanho efetivo do voxel, diminuindo a resolução espacial efetiva. Várias técnicas para redução de contaminação de lípidos têm sido propostas. Porém, estas apresentam algumas limitações. O objetivo deste estudo é desenvolver um novo método de pós-processamento que permita reduzir a contaminação do sinal dos lípidos extracerebrais nos espectros do cérebro usando conhecimento prévio da PSF. O método desenvolvido foi chamado Reduction of Lipid contamination with Zero-padding (REDLIPZ). Realizaram-se simulações com dados de MRSI simulados para testar o método e adquiriram-se dados de MRSI de fantomas e do cérebro para validação do método. Estes dados foram ainda usados para gerar dados com menor resolução. Utilizaram-se dois fantomas, um contendo água (fantoma de água), acetato, etanol e fosfato, simulando o sinal de metabolitos, e outro contendo óleo de girassol (fantoma de lípidos), simulando o sinal dos lípidos. Apenas no caso dos fantomas, foram feitas aquisições de referência (usando apenas o fantoma de água) onde não se aplicou qualquer supressão. Nas aquisições metabólicas para os fantomas (usando os dois fantomas) e in vivo, utilizou-se supressão de água com CHESS e supressão de lípidos com a crusher coil. Os dados do fantoma foram processados com e sem um filtro de apodização do espaço k, e os dados in vivo apenas com o filtro. Foi efetuada uma remoção do sinal residual da água com pós-processamento e não foi aplicada correção para a heterogeneidade de campo B1. Foram adquiridos mapas de lípidos e dos metabolitos para melhor visualizar alterações espaciais provocadas pelos métodos. Mapas da razão entre os picos dos metabolitos e dos lípidos também foram calculados, ilustrando alterações relativas para verificar se o método tem um maior efeito nos lípidos do que nos metabolitos. Avaliaram-se os espectros de diferentes voxels, um com baixa e outro com alta contaminação mostrando o efeito do método consoante o nível de contaminação. Comparou-se a razão acetato/etanol entre espectros da aquisição de referência (aquisição apenas com o fantoma de água) e da aquisição metabólica (aquisição com ambos os fantomas) para verificar se ambos os picos sofriam alterações de maneira uniforme após aplicação dos métodos. As comparações entre resultados do fantoma processados com e sem filtro mostram o efeito do método em ambos os dados. A comparação dos resultados dos dados originais com os de baixa resolução permite verificar como o método funcionaria com dados de menor resolução. Para este método é necessário assumir previamente que a propagação do sinal dos metabolitos é insignificante e que, por isso, este efeito pode ser desprezado. A utilização de um filtro de apodização do espaço k dificulta o cálculo de uma PSF mais verdadeira. A PSF estimada para os dados do fantoma processados com o filtro, terá lobos laterais diferentes e superiores aos da PSF real apodizada pelo filtro. A presença inesperada de sinal de metabolitos nas regiões correspondentes aos lípidos deve-se aos sinais de água e dos lípidos não totalmente suprimidos. Estes causam distorções da linha de base do espectro e, consequentemente, criam falsos sinais dos metabolitos. As maiores alterações provocadas pelo método nos voxels com maior contaminação, reforçam o facto das contribuições da PSF diminuírem com a distância ao centro da PSF. Verificou-se ainda que os diferentes metabolitos não são afetados uniformemente, porque a PSF difere para as várias ressonâncias. Nos dados de menor resolução foi observada uma menor redução do sinal dos lípidos e maiores artefactos de Gibbs ringing. Estes artefactos estão de acordo com o facto de que a PSF depende da resolução da imagem. Para dados de menor resolução a PSF apresenta lobos laterais maiores. Além disso é mais difícil definir o sinal dos lípidos responsável pela contaminação devido a efeitos de volume parcial e, por essa razão, a PSF produzida será menos precisa. Por último, a heterogeneidade de B1 causa uma variação espacial nos ângulos de nutação. A grande heterogeneidade de sinal deve-se ao facto de não ter sido aplicada uma correção para a heterogeneidade de B1. A correção é necessária no caso de serem feitas comparações diretas entre picos de diferentes metabolitos no espectro. Porém, a correção de B1 não é importante para o cálculo da PSF. A PSF depende da intensidade do sinal e se for aplicada correção de B1 antes de aplicar o método, a intensidade do sinal mudaria, mas a PSF calculada também mudará consoante essa alteração. Trabalho futuro incluirá a combinação dos dados de MRSI com imagens de alta resolução de MRI. Usando a imagem de MRI, o objetivo é realizar uma seleção mais precisa do sinal dos lípidos que realmente geram contaminação melhorando a estimação da PSF destes sinais. Também o perfil de sensibilidade das bobines de receção será tido em conta. A PSF é calculada com uma ponderação relativa à sensibilidade para cada uma das bobines, e no fim é feita uma soma de todas contribuições para cada voxel. Desta forma, produz-se um conhecimento prévio da PSF mais verdadeiro. O método desenvolvido neste estudo permitiu reduzir alguma contaminação dos lípidos em dados de MRSI do cérebro, através da determinação e subtração da PSF destes contaminantes dos espectros contaminados. A redução é benéfica e necessária para deteção e quantificação da concentração corretas dos metabolitos aumentando, assim, a relevância clinica das técnicas de MRSI.MR spectroscopic (MRS) imaging has relatively low spatial resolution and the reconstruction of the data requires a Fourier transform. As a result, MRS images suffer from an effect referred to as voxel bleeding, whereby residual extra-cranial lipid signals contaminate neighboring voxels. These signals can be one to two orders of magnitude higher than the metabolites, leading to a distortion of metabolite information as well as incorrect detection and quantification. Lipid contamination reduction is necessary to enable quantification of metabolite concentrations, thus, increasing the clinical relevance of MRSI techniques. To this end, our aim was to develop a post-processing method to reduce extra-cerebral lipid tissue signal contamination in the brain tissue spectra. In this work, a new post-processing approach to reduce extra-cerebral tissue lipid signal contamination in the brain tissue spectra by using prior PSF knowledge is presented. A method named REDLIPZ (REDuction of LIPid contamination with Zero-padding) was implemented to assess the PSF knowledge via zero-padding the k-space. The measured PSF of the contaminating lipid signal was later subtracted from the contaminated data. The REDLIPZ produced some reduction of the lipid signal with minimal variations (either an increase or a decrease) in the metabolite resonances both in phantom and in vivo MRSI data acquired at ultra-high field (7T). The reduction of the lipid signal was greater in generated data with lower resolution, however, the changes in the metabolite resonances were also larger. The method was proven to reduce some lipid contamination. This is beneficial for the clinical relevance of MRSI. Combining MRSI with high resolution MR images and taking into account the receiving coil array sensitivity profiles should be both considered for a more precise and truthful measure of the PSF. Further refinement including B1 correction and pre-processing of the MRSI data is required

Compressed Sensing Accelerated Magnetic Resonance Spectroscopic Imaging

abstract: Magnetic resonance spectroscopic imaging (MRSI) is a valuable technique for assessing the in vivo spatial profiles of metabolites like N-acetylaspartate (NAA), creatine, choline, and lactate. Changes in metabolite concentrations can help identify tissue heterogeneity, providing prognostic and diagnostic information to the clinician. The increased uptake of glucose by solid tumors as compared to normal tissues and its conversion to lactate can be exploited for tumor diagnostics, anti-cancer therapy, and in the detection of metastasis. Lactate levels in cancer cells are suggestive of altered metabolism, tumor recurrence, and poor outcome. A dedicated technique like MRSI could contribute to an improved assessment of metabolic abnormalities in the clinical setting, and introduce the possibility of employing non-invasive lactate imaging as a powerful prognostic marker. However, the long acquisition time in MRSI is a deterrent to its inclusion in clinical protocols due to associated costs, patient discomfort (especially in pediatric patients under anesthesia), and higher susceptibility to motion artifacts. Acceleration strategies like compressed sensing (CS) permit faithful reconstructions even when the k-space is undersampled well below the Nyquist limit. CS is apt for MRSI as spectroscopic data are inherently sparse in multiple dimensions of space and frequency in an appropriate transform domain, for e.g. the wavelet domain. The objective of this research was three-fold: firstly on the preclinical front, to prospectively speed-up spectrally-edited MRSI using CS for rapid mapping of lactate and capture associated changes in response to therapy. Secondly, to retrospectively evaluate CS-MRSI in pediatric patients scanned for various brain-related concerns. Thirdly, to implement prospective CS-MRSI acquisitions on a clinical magnetic resonance imaging (MRI) scanner for fast spectroscopic imaging studies. Both phantom and in vivo results demonstrated a reduction in the scan time by up to 80%, with the accelerated CS-MRSI reconstructions maintaining high spectral fidelity and statistically insignificant errors as compared to the fully sampled reference dataset. Optimization of CS parameters involved identifying an optimal sampling mask for CS-MRSI at each acceleration factor. It is envisioned that time-efficient MRSI realized with optimized CS acceleration would facilitate the clinical acceptance of routine MRSI exams for a quantitative mapping of important biomarkers.Dissertation/ThesisDoctoral Dissertation Bioengineering 201

A Longitudinal Study of Tumour Metabolism Using Hyperpolarized Carbon-13 Magnetic Resonance Spectroscopic Imaging in a Preclinical Model of Glioma

Glioma is the most common and aggressive primary malignant brain tumour. Glioma is typically treated with surgery followed by radio/chemotherapy. Even with aggressive treatment, median survival time is expected to be ~12 to 15 months. Reoccurrence of glioma is almost inevitable, further threatening the well-being of patients who have already endured rigorous treatment. Therefore, it is paramount to choose the most effective therapy and to accurately determine outcome as early as possible to provide optimum end-of-life care. Tumours alter their metabolism in response to increasing energy demands, mainly through increased glycolysis and accompanying lactate production. This increases production of other acids and alters intracellular and extracellular pH. Hyperpolarized 13C magnetic resonance spectroscopic imaging, is capable of measuring in vivo metabolism. Increased lactate production in tumours can be probed by imaging the metabolism of hyperpolarized [1-13C]pyruvate after injection. Similarly, extracellular pH can be mapped after measuring the concentrations of H13CO3- and 13CO2 after injection of hyperpolarized 13C bicarbonate. The objective of this thesis is to investigate molecular changes in lactate production and pH gradient in a rat glioma model. To accomplish this objective, three related projects have been undertaken. For first project, a custom-made switch-tunable radiofrequency coil was designed and constructed. This radiofrequency coil facilitated imaging 1H and 13C nuclei without any registration issues producing high signal-to-noise ratio imaging data. In the second project, C6 glioma was implanted into brains of rats, which were imaged with hyperpolarized [1-13C]pyruvate at days 7, 12, 15, 18, 21 and 24 after implantation. Between days 10 and 15, rats received one of three therapies: radiotherapy, chemotherapy, combined therapy or none. Significant early therapeutic response, measured as a reduction in the lactate-to-pyruvate ratio, was observed for effective therapy. In the final project, the same tumour model was used to study cellular pH gradient in tumours. Animals were monitored at days 8, 12 and 15 after implantation using hyperpolarized 13C bicarbonate to measure intracellular pH and a chemical exchange saturation transfer method to measure intracellular pH. Measured pH gradient in tumours showed a higher intracellular pH than extracellular pH, which was the opposite of healthy brain tissue. These studies have demonstrated the potential of hyperpolarized 13C probes to promptly measure changes in tumour metabolism. Early response assessment is important for identifying effective therapies and eliminating the toxic effects of ineffective ones. This can potentially reduce treatment costs for expensive and ineffective therapies and improve the quality of life for patients

Computer-Aided Detection and diagnosis for prostate cancer based on mono and multi-parametric MRI: A review

International audienceProstate cancer is the second most diagnosed cancer of men all over the world. In the last decades, new imaging techniques based on Magnetic Resonance Imaging (MRI) have been developed improving diagnosis.In practise, diagnosis can be affected by multiple factors such as observer variability and visibility and complexity of the lesions. In this regard, computer-aided detection and computer-aided diagnosis systemshave been designed to help radiologists in their clinical practice. Research on computer-aided systems specifically focused for prostate cancer is a young technology and has been part of a dynamic field ofresearch for the last ten years. This survey aims to provide a comprehensive review of the state of the art in this lapse of time, focusing on the different stages composing the work-flow of a computer-aidedsystem. We also provide a comparison between studies and a discussion about the potential avenues for future research. In addition, this paper presents a new public online dataset which is made available to theresearch community with the aim of providing a common evaluation framework to overcome some of the current limitations identified in this survey

In vivo magnetic resonance spectroscopy: basic methodology and clinical applications

The clinical use of in vivo magnetic resonance spectroscopy (MRS) has been limited for a long time, mainly due to its low sensitivity. However, with the advent of clinical MR systems with higher magnetic field strengths such as 3 Tesla, the development of better coils, and the design of optimized radio-frequency pulses, sensitivity has been considerably improved. Therefore, in vivo MRS has become a technique that is routinely used more and more in the clinic. In this review, the basic methodology of in vivo MRS is described—mainly focused on 1H MRS of the brain—with attention to hardware requirements, patient safety, acquisition methods, data post-processing, and quantification. Furthermore, examples of clinical applications of in vivo brain MRS in two interesting fields are described. First, together with a description of the major resonances present in brain MR spectra, several examples are presented of deviations from the normal spectral pattern associated with inborn errors of metabolism. Second, through examples of MR spectra of brain tumors, it is shown that MRS can play an important role in oncology